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pro vyhledávání: '"Khalili, N"'
The application of the Physics-Informed Neural Networks (PINNs) to forward and inverse analysis of pile-soil interaction problems is presented. The main challenge encountered in the Artificial Neural Network (ANN) modelling of pile-soil interaction i
Externí odkaz:
http://arxiv.org/abs/2212.08306
Publikováno v:
In Construction and Building Materials 8 March 2024 418
Publikováno v:
In International Journal of Solids and Structures 15 August 2023 277-278
Autor:
Khalili, N., Lessmann, N., Turk, E., Claessens, N., de Heus, R., Kolk, T., Viergever, M. A., Benders, M. J. N. L., Isgum, I.
MR images of fetuses allow clinicians to detect brain abnormalities in an early stage of development. The cornerstone of volumetric and morphologic analysis in fetal MRI is segmentation of the fetal brain into different tissue classes. Manual segment
Externí odkaz:
http://arxiv.org/abs/1906.04713
Automatic neonatal brain tissue segmentation in preterm born infants is a prerequisite for evaluation of brain development. However, automatic segmentation is often hampered by motion artifacts caused by infant head movements during image acquisition
Externí odkaz:
http://arxiv.org/abs/1906.04704
Publikováno v:
In Engineering Fracture Mechanics August 2022 271
Autor:
Khalili, N., Moeskops, P., Claessens, N. H. P., Scherpenzeel, S., Turk, E., de Heus, R., Benders, M. J. N. L., Viergever, M. A., Pluim, J. P. W., Išgum, I.
MR images of the fetus allow non-invasive analysis of the fetal brain. Quantitative analysis of fetal brain development requires automatic brain tissue segmentation that is typically preceded by segmentation of the intracranial volume (ICV). This is
Externí odkaz:
http://arxiv.org/abs/1708.02282
Publikováno v:
In Computers and Geotechnics October 2021 138
Publikováno v:
In Computer Methods in Applied Mechanics and Engineering 1 January 2021 373
Publikováno v:
In Engineering Fracture Mechanics January 2021 241